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|CMPS 130 - SCI PROBLEM SOLVING-PYTHON|
This course covers common computational approaches to solving scientific problems using the Python programming language. The first half of the course is dedicated to mastery of the Python language within the context of fundamental computer science topics, such object orientation, algorithmic complexity, recursion, and debugging/testing. The second half of the course focuses on practical scientific applications of Python in data analysis and experimentation. Students will develop programs using stochastic models, experimental probability and statistics, Monte Carlo simulation, regression analysis, and dynamic programming. PyLab, a graphing library similar to MatLab, will be utilized such that students can develop programs to report results using scatter plots, bar graphs, histograms, etc.
The course is specifically geared towards students with high aptitude in math, science, and critical thinking. Previous programming experience is recommended, but not required. The course will provide sufficient introduction to computer programming to the non-major, previous course work in computer science is not required. The course's emphasis on numerical problem-solving and data analysis, along with the introduction to the Python programming language, makes it a relevant and valuable course for computer science majors at the sophomore/junior level.
0.000 TO 4.000 Credit hours
0.000 TO 4.000 Lecture hours
Schedule Types: Hybrid, Lecture, Online Course
Computer Science Department